Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Containers, Kubernetes, Docker and related technologies.

Pepperdata In Collaboration with AWS | Optimize Utilization and Cost for Kubernetes Workloads

In this AWS Startup Partner Spotlight, discover how Pepperdata empowers cloud-native startups to optimize their Kubernetes and Amazon EMR workloads in real time. With automated resource optimization, companies can reduce costs by an average of 30% while increasing utilization by up to 80%—without any manual tuning. Whether you're scaling rapidly or managing unpredictable workloads, Pepperdata ensures your infrastructure runs efficiently and cost-effectively from day one.

Stop Guessing, Start Measuring: Optimizing Rancher Continuous Delivery With Fleet Benchmarks

Rancher Continuous Delivery (known as Fleet) can be used in a workflow to deploy applications to many clusters. With its GitOps support, it enables downstream clusters to pull updates from a Git repository. We know of users that monitor several hundred Git repositories and deploy to a thousand clusters. To make this scale possible, several intermediate steps are necessary. First, the application is converted into separate bundles, which are then targeted at clusters.

Why Manual Tuning Fails: A Better Way to Optimize Kubernetes Workloads

As a data platform engineer, you’re tasked with running complex workloads—Apache Spark jobs, AI/ML pipelines, batch ETL—across dynamic Kubernetes environments. Performance matters. Time spent tuning matters. And so does cost. But if you’re still relying on manual resource tuning to optimize your workloads, you’re playing a losing game. Sure, you can tweak CPU and memory requests by hand. You can comb through Prometheus metrics, look at job logs, estimate peaks.

New Feature: Virtual Providers - Orchestrate Hybrid Infrastructure

Your Infrastructure. Your Cloud. Anywhere. Introducing Virtual Providers—a powerful new way to turn any server or VM into part of your Cycle-managed private cloud. With just a bootable ISO generated from the Cycle platform, you can instantly bring bare metal or virtual machines online—no matter where they live. Cloud, colo, on-prem, edge, or even a server sitting in a closet. Once connected, Cycle handles the provisioning, updates, networking, and orchestration automatically.

NEW: Virtual Machines on Cycle

Run Anything, Anywhere — Now Including Virtual Machines Cycle just got even more powerful. In this video, we're announcing full support for virtual machine workloads on the Cycle platform. That means containers, functions, and now VMs—running side by side, managed through the same automation, networking, and orchestration engine. Whether it's bare metal in a colo, VMs on a cloud provider, or hardware in a homelab, Cycle brings it all together into one global private cloud.

Comprehensive Guide to Developing and Deploying a Python API with Docker and Kubernetes (Part I)

In the evolving landscape of software development, containerization and orchestration have become pivotal. Docker and Kubernetes stand at the forefront of this transformation, offering scalable and efficient solutions for application deployment. This guide provides a detailed walkthrough on developing a Python API, containerizing it with Docker, and deploying it using Kubernetes, ensuring a robust and production-ready application.

Our Biggest Platform Release in Years: Virtual Providers and Virtual Machines

Cycle.io is taking a giant leap forward in 2025. Today, we're announcing the biggest platform release in years -- a release that catapults Cycle into a new era of hybrid infrastructure orchestration and cements its status as a true alternative to both Kubernetes and VMware. Now, with two massively impactful features: Virtual Providers and Virtual Machines.

#043 - Gaming on K8s: Stateful Servers, Low Latency, and an Incredible Infra Journey with Siddha...

In this episode, Sid, CEO of Hathora, discusses building game infrastructure, specifically for hosting dedicated servers. He shares how Hathora tackles the challenges of running stateful, low-latency, high-throughput workloads that reconcile player actions up to 60 times per second. Sid explains their approach using Kubernetes to manage compute across bare metal and cloud VMs, leveraging technologies like Talos and Civo's Omni.